Object recognition by a self-organizing neural network which grows adaptively

J. Weng, T. S. Huang, N. Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe a new type of neural network for object recognition which we call a Cresceptron. The term “Cresceptron” was coined from Latin cresco (grow) and perceplio (perception). The primary objective of the Cresceptron framework is to automatically handle manually intractable tasks: such as constructing a network that can recognize many objects from real world images. The Cresceptron uses a hierarchical structure, and the network adaptivcly and incrementally grows through learning. For recognition, the network is made largely translationally invariant by using the same neuron at all the positions of each neural plane. Scale invariance is achieved through a multi-resolution representation with the framework of visual attention. Limited oricntational invariance is obtained by variation tolerance. Complete oricnlational invariance is not sought here since die recognition should report also the orientation. It is interesting to note that psychophysical studies have demonstrated that the human vision system does not have perfect invariance in cither translation, scale, or orientation.

Original languageEnglish (US)
Title of host publicationParallel Image Analysis - 2nd International Conference, ICPIA 1992, Proceedings
EditorsAkira Nakamura, Maurice Nivat, Ahmed Saoudi, Patrick S. P. Wang, Katsushi Inoue
PublisherSpringer-Verlag Berlin Heidelberg
Pages32-33
Number of pages2
ISBN (Print)9783540563464
DOIs
StatePublished - 1992
Event2nd International Conference on Parallel Image Analysis, ICPIA 1992 - Ube, Japan
Duration: Dec 21 1992Dec 23 1992

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume654 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Conference on Parallel Image Analysis, ICPIA 1992
CountryJapan
CityUbe
Period12/21/9212/23/92

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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